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Computer Assisted Language Learning Volume 37, 2024 - Issue 1-2
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Review

A review of AWE feedback: types, learning outcomes, and implications

Qing-Ke Fua School of Teacher Education, Huzhou University, Huzhou, PR ChinaORCID Iconhttps://orcid.org/0000-0002-9032-2905View further author information
ORCID Icon,
Di Zoub Department of English Language Education, The Education University of Hong Kong, Tai Po, Hong KongCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0001-8435-9739View further author information
ORCID Icon,
Haoran Xiec Department of Computing and Decision Sciences, Lingnan University, Tuen Mun, Hong KongORCID Iconhttps://orcid.org/0000-0003-0965-3617View further author information
ORCID Icon &
Gary Chengd Department of Mathematics and Information Technology, The Education University of Hong Kong, Tai Po, Hong KongORCID Iconhttps://orcid.org/0000-0002-5614-3348View further author information
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Pages 179-221 | Published online: 16 Feb 2022

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Appendix A. The coding schemesCoded papers

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  • Wilson, J., & Roscoe, R. D. (2020). Automated writing evaluation and feedback: Multiple metrics of efficacy. Journal of Educational Computing Research, 58(1), 87–125. https://doi.org/10.1177/0735633119830764
  • Zaini, A. (2018). Word processors as monarchs: Computer-generated feedback can exercise power over and influence EAL learners’ identity representations. Computers & Education, 120, 112–126. https://doi.org/10.1016/j.compedu.2018.01.014
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